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Fix push_to_hub docstring and make it appear in doc (#12770)

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This commit is contained in:
Sylvain Gugger
2021-07-17 15:52:33 +02:00
committed by GitHub
parent 08d609bfb8
commit da72ac6e26
9 changed files with 70 additions and 29 deletions
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1
docs/source/main_classes/configuration.rst
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@@ -22,4 +22,5 @@ PretrainedConfig
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.PretrainedConfig
:special-members: push_to_hub
:members:

3
docs/source/main_classes/model.rst
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@@ -35,6 +35,7 @@ PreTrainedModel
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.PreTrainedModel
:special-members: push_to_hub
:members:
@@ -80,6 +81,7 @@ TFPreTrainedModel
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.TFPreTrainedModel
:special-members: push_to_hub
:members:
@@ -94,6 +96,7 @@ FlaxPreTrainedModel
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.FlaxPreTrainedModel
:special-members: push_to_hub
:members:

12
docs/source/main_classes/tokenizer.rst
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@@ -53,10 +53,8 @@ PreTrainedTokenizer
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. autoclass:: transformers.PreTrainedTokenizer
:special-members: __call__
:members: batch_decode, convert_ids_to_tokens, convert_tokens_to_ids, convert_tokens_to_string, decode, encode,
get_added_vocab, get_special_tokens_mask, num_special_tokens_to_add, prepare_for_tokenization, tokenize,
vocab_size
:special-members: __call__, batch_decode, decode, encode, push_to_hub
:members:
PreTrainedTokenizerFast
@@ -68,10 +66,8 @@ loaded very simply into 🤗 transformers. Take a look at the :doc:`Using tokeni
<../fast_tokenizers>` page to understand how this is done.
.. autoclass:: transformers.PreTrainedTokenizerFast
:special-members: __call__
:members: batch_decode, convert_ids_to_tokens, convert_tokens_to_ids, convert_tokens_to_string, decode, encode,
get_added_vocab, get_special_tokens_mask, num_special_tokens_to_add,
set_truncation_and_padding,tokenize, vocab_size
:special-members: __call__, batch_decode, decode, encode, push_to_hub
:members:
BatchEncoding

16
src/transformers/configuration_utils.py
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@@ -22,7 +22,15 @@ import os
from typing import Any, Dict, Tuple, Union
from . import __version__
from .file_utils import CONFIG_NAME, PushToHubMixin, cached_path, hf_bucket_url, is_offline_mode, is_remote_url
from .file_utils import (
CONFIG_NAME,
PushToHubMixin,
cached_path,
copy_func,
hf_bucket_url,
is_offline_mode,
is_remote_url,
)
from .utils import logging
@@ -729,3 +737,9 @@ class PretrainedConfig(PushToHubMixin):
)
setattr(self, k, v)
PretrainedConfig.push_to_hub = copy_func(PretrainedConfig.push_to_hub)
PretrainedConfig.push_to_hub.__doc__ = PretrainedConfig.push_to_hub.__doc__.format(
object="config", object_class="AutoConfig", object_files="configuration file"
)

36
src/transformers/file_utils.py
View File

@@ -1991,14 +1991,14 @@ class PushToHubMixin:
use_auth_token: Optional[Union[bool, str]] = None,
) -> str:
"""
Upload model checkpoint or tokenizer files to the 🤗 Model Hub while synchronizing a local clone of the repo in
Upload the {object_files} to the 🤗 Model Hub while synchronizing a local clone of the repo in
:obj:`repo_path_or_name`.
Parameters:
repo_path_or_name (:obj:`str`, `optional`):
Can either be a repository name for your model or tokenizer in the Hub or a path to a local folder (in
which case the repository will have the name of that local folder). If not specified, will default to
the name given by :obj:`repo_url` and a local directory with that name will be created.
Can either be a repository name for your {object} in the Hub or a path to a local folder (in which case
the repository will have the name of that local folder). If not specified, will default to the name
given by :obj:`repo_url` and a local directory with that name will be created.
repo_url (:obj:`str`, `optional`):
Specify this in case you want to push to an existing repository in the hub. If unspecified, a new
repository will be created in your namespace (unless you specify an :obj:`organization`) with
@@ -2008,11 +2008,9 @@ class PushToHubMixin:
the current working directory. This will slow things down if you are making changes in an existing repo
since you will need to clone the repo before every push.
commit_message (:obj:`str`, `optional`):
Message to commit while pushing. Will default to :obj:`"add config"`, :obj:`"add tokenizer"` or
:obj:`"add model"` depending on the type of the class.
Message to commit while pushing. Will default to :obj:`"add {object}"`.
organization (:obj:`str`, `optional`):
Organization in which you want to push your model or tokenizer (you must be a member of this
organization).
Organization in which you want to push your {object} (you must be a member of this organization).
private (:obj:`bool`, `optional`):
Whether or not the repository created should be private (requires a paying subscription).
use_auth_token (:obj:`bool` or :obj:`str`, `optional`):
@@ -2022,29 +2020,27 @@ class PushToHubMixin:
Returns:
The url of the commit of your model in the given repository.
:obj:`str`: The url of the commit of your {object} in the given repository.
Examples::
# Upload a model to the Hub:
from transformers import AutoModel
from transformers import {object_class}
model = BertModel.from_pretrained("bert-base-cased")
# Fine-tuning code
{object} = {object_class}.from_pretrained("bert-base-cased")
# Push the model to your namespace with the name "my-finetuned-bert" and have a local clone in the
# Push the {object} to your namespace with the name "my-finetuned-bert" and have a local clone in the
# `my-finetuned-bert` folder.
model.push_to_hub("my-finetuned-bert")
{object}.push_to_hub("my-finetuned-bert")
# Push the model to your namespace with the name "my-finetuned-bert" with no local clone.
model.push_to_hub("my-finetuned-bert", use_temp_dir=True)
# Push the {object} to your namespace with the name "my-finetuned-bert" with no local clone.
{object}.push_to_hub("my-finetuned-bert", use_temp_dir=True)
# Push the model to an organization with the name "my-finetuned-bert" and have a local clone in the
# Push the {object} to an organization with the name "my-finetuned-bert" and have a local clone in the
# `my-finetuned-bert` folder.
model.push_to_hub("my-finetuned-bert", organization="huggingface")
{object}.push_to_hub("my-finetuned-bert", organization="huggingface")
# Make a change to an existing repo that has been cloned locally in `my-finetuned-bert`.
model.push_to_hub("my-finetuned-bert", repo_url="https://huggingface.co/sgugger/my-finetuned-bert")
{object}.push_to_hub("my-finetuned-bert", repo_url="https://huggingface.co/sgugger/my-finetuned-bert")
"""
if use_temp_dir:
# Make sure we use the right `repo_name` for the `repo_url` before replacing it.

7
src/transformers/modeling_flax_utils.py
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@@ -490,6 +490,13 @@ class FlaxPreTrainedModel(PushToHubMixin, FlaxGenerationMixin):
logger.info(f"Model pushed to the hub in this commit: {url}")
# To update the docstring, we need to copy the method, otherwise we change the original docstring.
FlaxPreTrainedModel.push_to_hub = copy_func(FlaxPreTrainedModel.push_to_hub)
FlaxPreTrainedModel.push_to_hub.__doc__ = FlaxPreTrainedModel.push_to_hub.__doc__.format(
object="model", object_class="FlaxAutoModel", object_files="model checkpoint"
)
def overwrite_call_docstring(model_class, docstring):
# copy __call__ function to be sure docstring is changed only for this function
model_class.__call__ = copy_func(model_class.__call__)

8
src/transformers/modeling_tf_utils.py
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@@ -36,6 +36,7 @@ from .file_utils import (
ModelOutput,
PushToHubMixin,
cached_path,
copy_func,
hf_bucket_url,
is_offline_mode,
is_remote_url,
@@ -1392,6 +1393,13 @@ class TFPreTrainedModel(tf.keras.Model, TFModelUtilsMixin, TFGenerationMixin, Pu
return model
# To update the docstring, we need to copy the method, otherwise we change the original docstring.
TFPreTrainedModel.push_to_hub = copy_func(TFPreTrainedModel.push_to_hub)
TFPreTrainedModel.push_to_hub.__doc__ = TFPreTrainedModel.push_to_hub.__doc__.format(
object="model", object_class="TFAutoModel", object_files="model checkpoint"
)
class TFConv1D(tf.keras.layers.Layer):
"""
1D-convolutional layer as defined by Radford et al. for OpenAI GPT (and also used in GPT-2).

8
src/transformers/modeling_utils.py
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@@ -38,6 +38,7 @@ from .file_utils import (
ModelOutput,
PushToHubMixin,
cached_path,
copy_func,
hf_bucket_url,
is_offline_mode,
is_remote_url,
@@ -1555,6 +1556,13 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin, GenerationMixin, PushToHubMix
return retrieved_modules
# To update the docstring, we need to copy the method, otherwise we change the original docstring.
PreTrainedModel.push_to_hub = copy_func(PreTrainedModel.push_to_hub)
PreTrainedModel.push_to_hub.__doc__ = PreTrainedModel.push_to_hub.__doc__.format(
object="model", object_class="AutoModel", object_files="model checkpoint"
)
class Conv1D(nn.Module):
"""
1D-convolutional layer as defined by Radford et al. for OpenAI GPT (and also used in GPT-2).

8
src/transformers/tokenization_utils_base.py
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@@ -43,6 +43,7 @@ from .file_utils import (
_is_torch_device,
add_end_docstrings,
cached_path,
copy_func,
hf_bucket_url,
is_flax_available,
is_offline_mode,
@@ -3371,3 +3372,10 @@ For a more complete example, see the implementation of `prepare_seq2seq_batch`.
)
model_inputs["labels"] = labels["input_ids"]
return model_inputs
# To update the docstring, we need to copy the method, otherwise we change the original docstring.
PreTrainedTokenizerBase.push_to_hub = copy_func(PreTrainedTokenizerBase.push_to_hub)
PreTrainedTokenizerBase.push_to_hub.__doc__ = PreTrainedTokenizerBase.push_to_hub.__doc__.format(
object="tokenizer", object_class="AutoTokenizer", object_files="tokenizer files"
)